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#Data analysis with excel vs python full
#Data analysis with excel vs python code

Excel reports can be instantly generated by R or Python (and others) to allow business people to play with data.

The solution is not going to be utilized across the company or its only role is being a scratchpad.

In practice that means that it might be a good idea to stay with spreadsheets, when:

The solution is temporary, and the spreadsheet will not require maintenance.

Optimizing user experience and the interface is not important.

Keeping well below this limit is necessary for everything to run smoothly. Microsoft suggests less than 30 concurrent users and Google also has its official limit of 100.

There’s no need for real-time updates or collaboration, or it is possible to use online spreadsheets (Office 365 or Google Docs) accepting their poor scalability.

Data is small and formulas are not extremely complicated.

Whilst the landscape for spreadsheets has changed, they do remain relevant under certain circumstances. Enter a number, enter an equation, and voila – you get results with no coding required. Part of the success of spreadsheets is the What You See Is What You Get (WYSIWYG) layout, which means that you’re dealing with a significantly reduced level of abstraction. Spreadsheet formulas are easy to create with only a handful of complex concepts like VLOOKUP or pivot tables.

#Data analysis with excel vs python code

Simply put: you can do complex work with spreadsheets without having to understand the fundamentals of computer science or code anything. A reactive model means that everything is recalculated in real-time, and when you add new formulas to your spreadsheet, you don’t need to think about the order of computations (as in most programming languages). The main advantages of spreadsheets are flexibility paired with a simple and powerful reactive computational model. Spreadsheets are an excellent tool and they have proved their usefulness for many decades in a variety of different contexts. We will then verify which of these are still relevant and which have changed as technology shifted. We are going to take a closer look at some of the root causes of the widespread success of spreadsheets. In this post, I am going to explain my take on when it is proper to use spreadsheets and when it is desirable to switch to more advanced technology. But this is only after losing money and time due to easily avoidable errors and the inevitable, ensuing chaos they bring. There is, however, a clear trend of companies switching to Excel alternatives.

#Data analysis with excel vs python full

While working with data, we have seen the full spectrum of use cases of Excel, including some truly scary ones. Even in 2021, many companies are still largely managed with spreadsheets.